Floodplain inundation and vegetation along the Negro and Amazon rivers near Manaus, Brazil were accurately delineated using multi-frequency, polarimetric synthetic aperture radar (SAR) data from the April and October 1994 SIR-C missions. A decision-tree model was used to formulate rules for a supervised classification into five categories: water, clearing (pasture), aquatic macrophyte (floating meadow), nonflooded forest, and flooded forest. Classified images were produced and tested within three days of SIR-C data acquisition. Both C-band (5.7 cm) and L-band (24 cm) wavelengths were necessary to distinguish the cover types. HH polarization was most useful for distinguishing flooded from nonflooded vegetation (C-HH for macrophyte versus pasture, and L-HH for flooded versus nonflooded forest), and cross-polarized L-band data provided the best separation between woody and nonwoody vegetation. Between the April and October missions, the Amazon River level fell about 3.6 m and the portion of the study area covered by flooded forest decreased from 23% to 12%. This study demonstrates the ability of multifrequency SAR to quantify in near realtime the extent of inundation on forested floodplains, and its potential application for timely monitoring of flood events